Continious variables involved in the following:
- Parallel coordinate plots
- Heatmaps
- Star charts
732A98
Continious variables involved in the following:
Construction:
Analysis: - Clusters - Outliers - Correlated variables
Example: Iris dataset - How many clusters do you see?
Problem formulation: Given data set
Note: possible orderings exist…
Solution: modern approaches
Objective functions:
They based on
Optimization algorithms:
Aim: distances should increase from diagonal
Hamiltonian path length:
Least squares criterion (PCA)
Partial enumeration methods
TSP solver
Hierarchical clustering
A heat map visualizes a matrix [ n x m]
Analysis:
If juxtaposed, analyse:
If superimposed,
Ordering:
Other positioning possible - PCA/MDS
Idea:
Analogy: cutting a sausage
Faceting = one more aesthetics
–> Useful tool for modeling!
facet_grid)facet_wrap)Example: Aids data (Age, Time of Death, Time of Diag)
Chapter 5
Paper "Hahsler, M., Hornik, K., & Buchta, C. (2008). Getting things in order: an introduction to the R package seriation. Journal of Statistical Software, 25(3), 1-34".
(Browse through) paper "Ankerst, M., Berchtold, S., & Keim, D. A. (1998, October). Similarity clustering of dimensions for an enhanced visualization of multidimensional data. In Information Visualization, 1998. Proceedings. IEEE Symposium on (pp. 52-60). IEEE."
Becker, R. A., Cleveland, W. S., & Shyu, M. J. (1996). The visual design and control of trellis display. Journal of computational and Graphical Statistics, 5(2), 123-155.